Jim Tobias Building a Web-based Mapping System for a Tuberculosis Genotyping Information Management System (5QaG&S):

Welcome to the first installment of GISandScience.com’s Five Questions about GIS and Science (5QaG&S).

GISandScience.com: Who are you and what do you do?

Jim Tobias: Jim Tobias, MS, GISP. I am currently building a web-based mapping system for a Tuberculosis (TB) Genotyping Information Management System for the US Centers for Disease Control and Prevention.

GISandScience.com: How did you get started with geospatial technology?

Jim Tobias: I started with geospatial technology in 1992 with NOAA and was supporting marine mammal research in the Gulf of Mexico and Caribbean.

GISandScience.com: How does geospatial technology help you do your job / scientific work?

Jim Tobias: Geospatial technology is critical to disease control and prevention and I am working to re-ignite interest in mapping in the spirit of Dr. John Snow and his investigations of cholera in London during the 1854 outbreak.

GISandScience.com: How important is a formal process/methodology (for example, the scientific method; the geographic approach) when using geospatial technology in your scientific work?

Jim Tobias: Perhaps the greatest part of the ArcGIS software is the ModelBuilder and the ability to build workflows with standard inputs, processes, and outputs that can all reside within a single geodatabase. This speaks to the Scientific Method and allows researchers to run analyses and then zip and ship those inputs, models, and outputs to other researchers where experiments can be replicated, vetted, and examined with transparency of process.

GISandScience.com: What features or capabilities would make geospatial technology even more valuable for scientific work?

Jim Tobias: The Model Builder should be expanded and should begin to offer a full visual programming environment such as Orange Data Mining tools. The Orange Data Mining tools allow visual programming of drag-and-drop Python widgets that encapsulate analytic methods in the spirit of Dr. John Tukey and his Exploratory Data Analysis. The Python widgets can be strung together visually and used to create programs that I would challenge a hard-coding programmer to build in several weeks. It is possible to build very robust visual EDA and ESDA models and workflows and applications within a matter of 15 minutes using the Orange Canvas and visual programming techniques. These models and applications can be rapidly shared and are all Python and so one begins to build a Swiss watch with transparent gears that any scientist can examine, modify, and a framework to build upon for future analytics. A similar environment is the KNIME and the TAVERNA project. These folks have all recognized that the pace of science can be accelerated and built within an open, transparent, and replicable environment that caters to the Scientific Method.

If you are a scientist working with geospatial technologies and would like to participate is the 5QaG&S interview series, please email me at martz(at)esri(dot)com.